Modelling soil emissions and precision agriculture in fertilization life cycle assessment - A case study of wheat production in Austria

https://doi.org/10.1016/j.jclepro.2022.134841Get rights and content
Under a Creative Commons license
open access

Highlights

  • Life cycle assessment is used with the DeNitrification-DeComposition soil model.

  • Emissions estimated by the soil model are lower than those in ecoinvent.

  • Fertilizer application drives indirect soil emissions more than direct emissions.

  • A crop sensor reduced the global warming potential of fertilization by 8.6%.

  • Negligible impacts arise from precision agriculture sensor and ICT components.

Abstract

The environmental assessment of using optical crop sensors for variable rate nitrogen application (VRNA) has been limited by the lack of a robust method to quantify site- and technology-specific impacts. This study aimed to (1) present a comparative life cycle assessment (LCA) of a conventional winter wheat production system with and without using a crop sensor for VRNA applied to an Austrian case study. Special emphasis was placed on simulating site-specific field emissions with the DeNitrification-DeComposition (DNDC) biogeochemical soil model; (2) assess the environmental impacts of only the fertilization process; and (3) compare soil emissions simulated by the DNDC with soil emissions coming from a benchmark ecoinvent wheat production process. Three nitrogen fertilization schemes – one conventional and two VRNA – were modeled. Two functional units were used – 1 ha of cultivated winter wheat and 1 kg of winter wheat produced. The system boundary includes tillage, seeding, plant protection, nitrogen fertilization, and harvesting processes. Information communication technologies (ICT) – manufacturing of the sensor, internet and computer manufacturing and usage – were also included within the boundary. Local and global environmental impacts attributed to nitrogen emissions due to fertilization were evaluated in this LCA, including climate change (CC), fine particulate matter formation (FPMF), freshwater eutrophication (FE), freshwater ecotoxicity (FET), terrestrial acidification (TA), marine eutrophication (ME), and human noncarcinogenic toxicity (HTnc). The CC of the fertilization process was 1,662.8 kg CO2 eq./ha with conventional nitrogen application versus 1,518.8 kg CO2 eq./ha as the lower of the two VRNA results, an 8.6% reduction due to less fertilizer applied. Fertilization was found to be responsible for more than 80% of the total emissions that impact CC, 55% of the FET, 44% of the HTnc, 96% of the FE and 96% of the TA. The largest greenhouse gas (GHG) emitters were soil N emissions as simulated by the DNDC, followed by the fertilizer manufacturing process in all of the impacts, except for FET and HTnc, where fertilizer production was the highest contributor. ICT components contributed less than 1% to all of the impacts assessed. The amount of applied N fertilizer has a greater influence on NH3 and NO3 indirect soil emissions than on direct N2O emissions. This study demonstrates that using optical crop sensors for VRNA could have a limited but positive environmental impact and highlights the importance of applying site-specific soil models to estimate field emissions.

Keywords

Life cycle assessment (LCA)
Sustainability assessment
DeNitrification-DeComposition (DNDC)
Smart farming ∙ precision agriculture
Crop sensor

Data availability

No data was used for the research described in the article.

Cited by (0)